Applications such as those that attempt to detect pirated content conveyed by video and audio signals or that attempt to resynchronize disassociated video and audio signals often rely on processes that examine signal content to identify the signals. For many of these applications, it is important to obtain a reliable identification of signals even when the content of those signals has been modified either unintentionally or intentionally such that the modified content can still be recognized by a human observer as being substantially the same as the original content. If the perceived difference between the content of an original signal and a modified signal is small, then preferably the identification process can extract identifying features from the original and modified signals that are very similar to one another.
Examples of unintentional modifications to signal content include the insertion or addition of noise to signals in transmission channels and on storage media. Examples of intentional modifications to video signals include luminance and color modifications such as contrast/brightness adjustments, gamma correction, luminance histogram equalization, color saturation adjustments and color correction for white balancing, include geometric modifications such as image cropping and resizing, image rotation and flipping, stretching, speck removal, blurring, sharpening and edge enhancement, and include coding techniques such as lossy compression. Examples of intentional modifications to audio signals include amplification, equalization, dynamic range modification, channel up-mixing, time-scale modification, spectral shaping and lossy data compression.